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The aquatic environment of the coastal Arctic is rapidly changing, and understanding how this change will affect the coastal ocean is critical across sectors. To address this, a three-dimensional (3-D) hydrodynamic model was constructed, spanning the coastal Beaufort Sea from −153° to −142° W, explicitly including river delta channels and lagoons, and extending to the continental shelf. The Finite Volume Community Ocean Model (FVCOM) was used to predict ocean physical properties from January 2018 to September 2022, including dynamic sea ice and landfast ice. Model calibration and validation were conducted using a variety of data sources, includingin situhydrodynamic data from oceanographic cruises and moorings. Overall, the model captured interannual temperature variation at Prudhoe Bay from 2018 to 2022 with a model efficiency (MEF) score > 0 (better than the average) for all years (MEF = 0.59, 0.63, 0.23, 0.46, and 0.55). The seasonal temperatures in 2018 and 2019 at bottom-mounted moorings were also well captured (R²= 0.80–0.90), and sea surface height (SSH) was compared to hourly observations at Prudhoe Bay, with both the low-frequency (R²= 0.42) and diurnal (R²= 0.71) variations validated over the model period. Modeled salinity and water current velocity had mixed results compared to the observations: seasonal trends in salinity were generally captured well, but hypersaline lagoon conditions in the winter were not replicated. Measured bottom water velocity proved difficult to recreate within the model for any given point in time from 2018 to 2019. Covariance analyses of the surface wind velocity, SSH, and current velocity indicated that wind forcing significantly correlated to errors in local SSH predictions. Current velocity covaried substantially less with SSH and wind velocity, with large differences across the three moorings: this suggests that local factors such as bathymetry and shielding by islands are likely important. Future work building on this system will include analyses of the drivers of landfast ice and sea ice breakup; the potential for erosion via waves, large storms, and elevated surface temperatures; and the linkage to an ecosystem model that represents processes from carbon cycling to higher trophic levels. 

Abstract The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount ofin situdata to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophylla, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA thede-factostate of knowledge ofin situcoastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.